Exclusive Research Study on Big Data and Analytics Industry

Exclusive Research Study on Big Data and Analytics Industry

Big data is an area that addresses ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be processed by traditional data processing application software. Data with many fields (columns) provides greater statistical performance, while data with greater complexity (more attributes or columns) can result in a higher false detection rate. Big data analytics challenges include data collection, data storage, data analysis, search, sharing, transfer, visualization, query, update, data protection, and data source.

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Some of the key players of Big Data and Analytics Industry:

Microsoft, MongoDB, Predikto, Informatica, CS, Blue Yonder, Azure, Software AG, Sensewaves, TempoIQ, SAP, OT, IBM, Cyber Group, Splunk

Big data was originally associated with three key concepts: volume, diversity, and speed. The analysis of big data poses challenges when it comes to sampling and so far has only enabled observations and sampling. As a result, big data often contains data that is larger than traditional software can handle in an acceptable time and value.

Current usage of the term big data usually refers to the use of predictive analytics, user behavior analytics, or certain other advanced data analysis methods that extract value from big data, and rarely to a specific size of data set. "There is little doubt that the amount of data available now is actually large, but that is not the most relevant feature of this new data ecosystem." Analyzing datasets can find new correlations to "identify business trends, prevent disease, fight crime, and so on."

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